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Article recommendation method and device based on knowledge graph, electronic equipment and medium

A technology of knowledge graph and recommendation method, applied in the field of item recommendation, can solve problems such as performance degradation and low algorithm accuracy, and achieve the effect of improving user satisfaction

Pending Publication Date: 2021-06-22
BOE TECH GRP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of the shortcomings of the existing methods, this application proposes an item recommendation method, device, electronic equipment, and medium based on knowledge graphs to solve the problem that the existing recommendation methods are prone to performance degradation due to too sparse user behavior matrix or due to neglect of users. Behavior that leads to technical problems with low accuracy of the algorithm

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  • Article recommendation method and device based on knowledge graph, electronic equipment and medium
  • Article recommendation method and device based on knowledge graph, electronic equipment and medium
  • Article recommendation method and device based on knowledge graph, electronic equipment and medium

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Embodiment Construction

[0026] The present application is described in detail below, and examples of embodiments of the present application are shown in the drawings, wherein the same or similar reference numerals denote the same or similar components or components having the same or similar functions throughout. Also, detailed descriptions of known technologies will be omitted if they are not necessary to illustrate the features of the present application. The embodiments described below by referring to the figures are exemplary only for explaining the present application, and are not construed as limiting the present application.

[0027] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meanings as commonly understood by those of ordinary skill in the art to which this application belongs. It should also be understood that terms, such as those defined in commonly used dictionaries, should be ...

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Abstract

The invention provides an article recommendation method and device based on a knowledge graph, electronic equipment and a medium. The method comprises the following steps: determining a semantic-based first similarity between any two articles according to a knowledge graph of a plurality of articles; according to the user score of each article, determining a second similarity between any two articles based on the user behavior; according to the first similarity and the second similarity between the non-behaved articles of each user and the behaved articles and the user score of the behaved articles of each user, determining a predicted score of each user on the non-behaved articles; According to the predicted score of each user on the items which do not generate the behaviors, determining a recommendation list of the items which do not generate the behaviors for each user, and pushing the recommendation list to a terminal of the corresponding user. The article with a high prediction score can be recommended to the user as an article conforming to user preferences, habits and personalized requirements, and the user is helped to make a decision quickly.

Description

technical field [0001] The present application relates to the technical field of item recommendation, and in particular, the present application relates to a method, device, electronic device, and medium for item recommendation based on knowledge graphs. Background technique [0002] The recommendation system can predict the user's preference for the product according to the user's preferences, habits, individual needs and product characteristics without the need for the user to explicitly provide the content they want, and recommend the most suitable product for the user. [0003] Existing recommendation systems usually adopt collaborative filtering or content-based recommendation. The collaborative filtering method is prone to performance degradation due to the user behavior matrix being too sparse, and there is a cold start problem that cannot recommend new items; the content-based recommendation method pays attention to the content information of the item itself and igno...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06Q30/06G06F16/28G06F40/30G06K9/62
CPCG06F16/9535G06Q30/0631G06F16/288G06F18/22
Inventor 李慧周希波
Owner BOE TECH GRP CO LTD